Analysis of Circumcision Data

Author

Sean Pascoe

Published

April 29, 2024

Code

library(tidyverse)
library(patchwork)
library(DT)
source("R_scripts/functions/pairwise_comparisons.R")

Background

In this study, shave biopsies were collected from both the glans and shaft of circumcised/uncircumcised donors. Some biopsies were then cultured for 4 hours with HIV, and others were kept as uninfected controls. Tissue samples were stained and imaged and virus particles were counted. Samples were also later sent to the pathology core to be stained for CD117 and tryptase, in order to identify possible mast cell presence or difference in localization in these samples. Throughout the analysis, we look at the different distribution of virions and immune cells in these different conditions to investigate the immune cell dynamics in uncircumcised and circumcised penis tissue.

Virion Particle count

First, we can look at the distribution of individual virions between conditions. Our virion counts followed a negative binomial distribution, and thus we use negative binomial models to compare them and measure estimated marginal means.

Here we see the mean number of virions found in each condition:

Code

load("figures/plots/mean_virus_counts.rda")
mean_virus_counts

There is no significance here, but this probably makes sense, as the number of virions in an infected condition likely reflects experimental parameters rather than differential treatement of the virions by immune cells in the 4 hour period.

Instead, we can look at just penetrating virions as the percent of total virions introduced. On first glance, it seems like circumcised donors have slightly higher levels of complete rejection:

Code

load("figures/plots/rejected_virions_plot.rda")
rejected_virions_plot

We can also model the percent of penetrating virions, and we see that there may be a difference between circumcised and uncircumcised here. Notably, we do see a difference when we don’t take the mean per donor, however, the mean per donor data is (unsignificant) but more aligned with the hypothesis that we would see a difference in glans but not in shaft:

Code

load("figures/plots/penetrators_nomean_plot.rda")
load("figures/plots/mean_penetrators_plot.rda")
load("figures/plots/mean_penetrators_plot_phack.rda")

p0 <- penetrators_nomean_plot +
  labs(title = "% Penetrators per Image")

p1 <- mean_penetrators_plot +
  labs(title = "% Penetrators per Donor")

p1_hack <- mean_penetrators_plot_phack +
  labs(title = "% Penetrators per Donor (p hacking!)")

p0 + p1

Here I am more tempted to believe the per donor analysis. If we don’t correct for multiple hypothesis tests when we calculate p values, the difference between circumcised and uncircumcised within glans (but not shaft!) is signficant. Sure, this is p hacking, but if god wanted statistics to be rigorous he wouldn’t have invented stat_pvalue_manual().

Code

p1 + p1_hack

We also have data here for the depth that virions penetrated– but it looks generally the same between our samples.

Code

load("figures/plots/depth_distribution.rda")
depth_distribution

When we model this, do we see significant differences?

Code

load("figures/plots/mean_depth_plot.rda")
mean_depth_plot

No.

Mast Cell Count Analysis

We can also look at the differences in distributions of tryptase and CD117, both of which should be mast cell markers, in these tissue samples. Here, we now also examine the difference between samples that were infected for 4h, and uninfected controls.

Infected vs Uninfected

We start by building a mixed effect model of the uninfected data:

Code

load("data/processed/tryptase.rda")
non_infected <- tryptase |>
  filter(group == "Non Infected") |>
  group_by(condition, tissue, target_cell, donor) |>
  summarize(mean_percent_pos_by_area = mean(percent_pos_by_area))

non_infected_model <-
  lme4::lmer(
    log10(mean_percent_pos_by_area) ~ condition * tissue * target_cell + (1 | donor),
    data = non_infected
  )

compare_all_pairs(non_infected_model, factors = c('tissue', 'condition', 'target_cell')) |>
  display_comparison_table(title = "Non Infected Samples Model")

Non Infected Samples Model
condition	target_cell	contrast	tissue	estimate	SE	d.f.	t-ratio	p value
.	.	Glans - Shaft	.	-0.07	0.05	105.58	-1.53	0.21728
Circumcised	.	Glans - Shaft	.	-0.22	0.06	102.44	-3.54	0.00827
Uncircumcised	.	Glans - Shaft	.	0.08	0.07	108.15	1.14	0.33261
.	CD117	Glans - Shaft	.	-0.12	0.06	102.98	-1.80	0.18048
.	Tryptase	Glans - Shaft	.	-0.02	0.06	102.98	-0.38	0.82649
Circumcised	CD117	Glans - Shaft	.	-0.26	0.09	101.38	-2.94	0.02392
Uncircumcised	CD117	Glans - Shaft	.	0.02	0.10	104.32	0.24	0.88804
Circumcised	Tryptase	Glans - Shaft	.	-0.18	0.09	101.38	-2.08	0.12109
Uncircumcised	Tryptase	Glans - Shaft	.	0.13	0.10	104.32	1.38	0.25622
.	.	Circumcised - Uncircumcised	.	0.00	0.07	35.75	-0.04	0.96872
.	.	Circumcised - Uncircumcised	Glans	-0.15	0.09	68.12	-1.76	0.18048
.	.	Circumcised - Uncircumcised	Shaft	0.15	0.08	65.18	1.74	0.18048
.	CD117	Circumcised - Uncircumcised	.	-0.02	0.08	67.02	-0.23	0.88804
.	Tryptase	Circumcised - Uncircumcised	.	0.01	0.08	67.02	0.16	0.90777
.	CD117	Circumcised - Uncircumcised	Glans	-0.16	0.11	116.17	-1.48	0.22652
.	CD117	Circumcised - Uncircumcised	Shaft	0.12	0.10	113.54	1.15	0.33261
.	Tryptase	Circumcised - Uncircumcised	Glans	-0.14	0.11	116.17	-1.33	0.26456
.	Tryptase	Circumcised - Uncircumcised	Shaft	0.17	0.10	113.54	1.62	0.19453
.	.	CD117 - Tryptase	.	-0.16	0.05	100.31	-3.59	0.00827
.	.	CD117 - Tryptase	Glans	-0.21	0.07	100.31	-3.21	0.01629
.	.	CD117 - Tryptase	Shaft	-0.12	0.06	100.31	-1.85	0.18048
Circumcised	.	CD117 - Tryptase	.	-0.18	0.06	100.31	-2.91	0.02392
Uncircumcised	.	CD117 - Tryptase	.	-0.15	0.07	100.31	-2.19	0.11801
Circumcised	.	CD117 - Tryptase	Glans	-0.22	0.09	100.31	-2.46	0.07027
Circumcised	.	CD117 - Tryptase	Shaft	-0.14	0.09	100.31	-1.65	0.19453
Uncircumcised	.	CD117 - Tryptase	Glans	-0.20	0.10	100.31	-2.09	0.12109
Uncircumcised	.	CD117 - Tryptase	Shaft	-0.09	0.09	100.31	-0.99	0.39697
P value adjustment: FDR

We can view the signficant differences, contrasted with the nonsignificant ones:

Code

load("figures/plots/non_infected_plot.rda")
non_infected_plot

We can then compare this to a mixed effects model built from the infected samples:

Code

infected <- tryptase |>
  filter(group == "4h HIV") |>
  group_by(condition, tissue, target_cell, donor) |>
  summarize(mean_percent_pos_by_area = mean(percent_pos_by_area))

infected_model <-
  lme4::lmer(
    log10(mean_percent_pos_by_area) ~ condition * tissue * target_cell + (1|donor),
    data = infected
  )

compare_all_pairs(infected_model, factors = c('tissue', 'condition', 'target_cell')) |>
  display_comparison_table(title = "Infected Samples Model")

Infected Samples Model
condition	target_cell	contrast	tissue	estimate	SE	d.f.	t-ratio	p value
.	.	Glans - Shaft	.	-0.11	0.04	97.02	-2.83	0.01704
Circumcised	.	Glans - Shaft	.	-0.21	0.05	99.98	-3.83	0.00154
Uncircumcised	.	Glans - Shaft	.	-0.01	0.05	93.97	-0.15	0.88124
.	CD117	Glans - Shaft	.	-0.14	0.05	94.52	-2.62	0.02123
.	Tryptase	Glans - Shaft	.	-0.08	0.05	95.27	-1.43	0.26417
Circumcised	CD117	Glans - Shaft	.	-0.21	0.08	95.90	-2.74	0.01794
Uncircumcised	CD117	Glans - Shaft	.	-0.07	0.08	93.14	-0.96	0.47999
Circumcised	Tryptase	Glans - Shaft	.	-0.21	0.08	97.42	-2.78	0.01773
Uncircumcised	Tryptase	Glans - Shaft	.	0.06	0.08	93.14	0.75	0.55814
.	.	Circumcised - Uncircumcised	.	-0.02	0.08	34.52	-0.28	0.84627
.	.	Circumcised - Uncircumcised	Glans	-0.12	0.09	53.99	-1.39	0.26868
.	.	Circumcised - Uncircumcised	Shaft	0.08	0.09	49.59	0.93	0.48516
.	CD117	Circumcised - Uncircumcised	.	-0.02	0.09	51.74	-0.27	0.84627
.	Tryptase	Circumcised - Uncircumcised	.	-0.02	0.09	51.23	-0.24	0.84627
.	CD117	Circumcised - Uncircumcised	Glans	-0.09	0.10	87.41	-0.88	0.48695
.	CD117	Circumcised - Uncircumcised	Shaft	0.04	0.10	82.06	0.44	0.77627
.	Tryptase	Circumcised - Uncircumcised	Glans	-0.15	0.10	87.41	-1.49	0.25278
.	Tryptase	Circumcised - Uncircumcised	Shaft	0.11	0.10	80.65	1.14	0.38357
.	.	CD117 - Tryptase	.	-0.20	0.04	92.67	-5.38	0.00002
.	.	CD117 - Tryptase	Glans	-0.23	0.05	92.30	-4.31	0.00055
.	.	CD117 - Tryptase	Shaft	-0.17	0.05	93.08	-3.28	0.00571
Circumcised	.	CD117 - Tryptase	.	-0.20	0.05	93.05	-3.87	0.00154
Uncircumcised	.	CD117 - Tryptase	.	-0.20	0.05	92.30	-3.74	0.00172
Circumcised	.	CD117 - Tryptase	Glans	-0.20	0.08	92.30	-2.64	0.02123
Circumcised	.	CD117 - Tryptase	Shaft	-0.20	0.07	93.92	-2.84	0.01704
Uncircumcised	.	CD117 - Tryptase	Glans	-0.27	0.08	92.30	-3.45	0.00376
Uncircumcised	.	CD117 - Tryptase	Shaft	-0.13	0.07	92.30	-1.81	0.14162
P value adjustment: FDR

And can visualize those differences:

Code

load("figures/plots/infected_tryp_plot.rda")
infected_tryp_plot

Glans vs Shaft

If we want to directly compare infected and uninfected samples, we need to make sure we only have paired samples (those from the same donor).

We first build a mixed effects model looking at differences within glans:

Code

Donors_w4h <- unique(filter(tryptase, group == "4h HIV")$donor)

tryptase_paired <-
  tryptase %>% 
  filter(donor %in% Donors_w4h)


paired_glans <- tryptase_paired |> 
  filter(tissue == "Glans") |>
  group_by(condition, tissue, target_cell, group, donor) |>
  summarize(mean_percent_pos_by_area = mean(percent_pos_by_area))

paired_glans_model <-
  lme4::lmer(
    log10(mean_percent_pos_by_area) ~ condition * group * target_cell + (1|donor),
    data = paired_glans
  )

comps_to_make <- c("group",
                   "condition",
                   "target_cell",
                   "condition | group | target_cell",
                   "target_cell | condition | group",
                   "group | condition | target_cell")

comparisons_made <- compare_pairs(paired_glans_model, 
                                  comparisons = comps_to_make,
                                  p_adjustment = 'fdr')

display_comparison_table(comparisons_made)

summary table
group	target_cell	condition	contrast	estimate	SE	d.f.	t-ratio	p value
.	.	.	4h HIV - Non Infected	-0.18	0.04	92.84	-4.16	0.00053
.	.	.	Circumcised - Uncircumcised	-0.15	0.09	34.01	-1.69	0.13708
.	.	.	CD117 - Tryptase	-0.21	0.04	86.18	-5.09	0.00003
4h HIV	CD117	.	Circumcised - Uncircumcised	-0.14	0.12	77.64	-1.19	0.25633
Non Infected	CD117	.	Circumcised - Uncircumcised	-0.16	0.12	79.65	-1.39	0.21022
4h HIV	Tryptase	.	Circumcised - Uncircumcised	-0.20	0.12	77.64	-1.72	0.13305
Non Infected	Tryptase	.	Circumcised - Uncircumcised	-0.11	0.12	79.65	-0.95	0.34420
4h HIV	.	Circumcised	CD117 - Tryptase	-0.20	0.08	86.18	-2.45	0.03721
4h HIV	.	Uncircumcised	CD117 - Tryptase	-0.27	0.08	86.18	-3.21	0.00935
Non Infected	.	Circumcised	CD117 - Tryptase	-0.22	0.08	86.18	-2.85	0.02044
Non Infected	.	Uncircumcised	CD117 - Tryptase	-0.16	0.09	86.18	-1.80	0.12672
.	CD117	Circumcised	4h HIV - Non Infected	-0.19	0.08	88.20	-2.37	0.03721
.	CD117	Uncircumcised	4h HIV - Non Infected	-0.22	0.09	90.83	-2.40	0.03721
.	Tryptase	Circumcised	4h HIV - Non Infected	-0.20	0.08	88.20	-2.54	0.03721
.	Tryptase	Uncircumcised	4h HIV - Non Infected	-0.12	0.09	90.83	-1.29	0.23142
P value adjustment: FDR

We can then visualize these differences:

Code

load("figures/plots/glans_tryp_plot.rda")
glans_tryp_plot

And we can then also look to see what differences we have in samples from shaft:

Code

paired_shaft <- tryptase_paired |> 
  filter(tissue == "Shaft") |>
  group_by(condition, tissue, target_cell,group, donor) |>
  summarize(mean_percent_pos_by_area = mean(percent_pos_by_area))

paired_shaft_model <-
  lme4::lmer(
    log10(mean_percent_pos_by_area) ~ condition * group * target_cell + (1|donor),
    data = paired_shaft
  )

comps_to_make <- c("group",
                  "condition",
                  "target_cell",
                  "condition | group | target_cell",
                  "target_cell | condition | group",
                  "group | condition | target_cell")

comparisons_made <- compare_pairs(paired_shaft_model, 
                                  comparisons = comps_to_make,
                                  p_adjustment = 'fdr')

display_comparison_table(comparisons_made)

summary table
group	target_cell	condition	contrast	estimate	SE	d.f.	t-ratio	p value
.	.	.	4h HIV - Non Infected	-0.13	0.04	99.88	-3.28	0.01071
.	.	.	Circumcised - Uncircumcised	0.12	0.07	35.18	1.68	0.17053
.	.	.	CD117 - Tryptase	-0.14	0.04	94.35	-3.54	0.00933
4h HIV	CD117	.	Circumcised - Uncircumcised	0.03	0.10	94.67	0.35	0.73003
Non Infected	CD117	.	Circumcised - Uncircumcised	0.14	0.10	100.58	1.36	0.26560
4h HIV	Tryptase	.	Circumcised - Uncircumcised	0.11	0.10	93.00	1.11	0.33849
Non Infected	Tryptase	.	Circumcised - Uncircumcised	0.20	0.10	100.58	1.99	0.11577
4h HIV	.	Circumcised	CD117 - Tryptase	-0.21	0.08	94.78	-2.76	0.02592
4h HIV	.	Uncircumcised	CD117 - Tryptase	-0.13	0.08	94.23	-1.72	0.16692
Non Infected	.	Circumcised	CD117 - Tryptase	-0.14	0.07	94.23	-1.95	0.11577
Non Infected	.	Uncircumcised	CD117 - Tryptase	-0.08	0.09	94.23	-0.86	0.45352
.	CD117	Circumcised	4h HIV - Non Infected	-0.22	0.07	95.62	-2.90	0.02298
.	CD117	Uncircumcised	4h HIV - Non Infected	-0.11	0.09	98.55	-1.30	0.26654
.	Tryptase	Circumcised	4h HIV - Non Infected	-0.15	0.07	95.08	-2.04	0.11577
.	Tryptase	Uncircumcised	4h HIV - Non Infected	-0.05	0.09	98.55	-0.63	0.56764
P value adjustment: FDR

And we can visualize these:

Code

load("figures/plots/shaft_tryp_plot.rda")
shaft_tryp_plot

These two are interesting in tandem, because (taken as a binary for their statistical significance) there is an indication that there are fewer tryptase expressing cells in in circumcised glans, but not in circumcised shaft, when comparing between infected and non infected cells. In the context of our hypothesis, this might imply that a lower rate of HIV acquisition in circumcised men is related to a more prominent reduction in tryptase levels in response to HIV innoculation.

Still, these are p values close to 0.05, and we might have to follow this with more targeted experimentation to figure out if this is signal or noise.

Immunofluorescence Cell Distribution

Finally, we turn to data from the immunofluorescence experiment, in which these samples of glans/shaft had been stained with CD3, CD4, and CCR10. These cells were then counted, and measured as distance from the epithelium. A representative image is included:

Approximate cell types based on these markers are delineated below:

Code

tribble(
  ~ "IF Expression", ~ "Expected Cell Type",
  "CD3+CD4+CCR10+", "Th22 (Tissue Homing T cell)",
  "CD3+CCR10+", "CD8+ Cutaneous Lymphoid Antigen T cell",
  "CD4+CCR10+", "Langerhans skin cell",
  "CD3+CD4+", "CD4+ T cell (likely Th1, Th2, Th9, or Th17)",
  "CD3+", "Other T cell",
  "CD4+", "HIV susceptible innate immune cells (macrophages, mast cells, etc)",
  "CCR10+", "Melanocytes"
) |>
  gt::gt() |>
  gt::tab_header(title = "Expected IF Cell Types")

Expected IF Cell Types
IF Expression	Expected Cell Type
CD3+CD4+CCR10+	Th22 (Tissue Homing T cell)
CD3+CCR10+	CD8+ Cutaneous Lymphoid Antigen T cell
CD4+CCR10+	Langerhans skin cell
CD3+CD4+	CD4+ T cell (likely Th1, Th2, Th9, or Th17)
CD3+	Other T cell
CD4+	HIV susceptible innate immune cells (macrophages, mast cells, etc)
CCR10+	Melanocytes

Here, looking at the number of cells per sample isn’t the most interesting, as this is likely just a result of how the tissue was cut. What would be interesting would be to look at if the distribution, i.e. how far any particular cell type was from the beginning of the epithelial layer, of these cells changed as a result of the virion infection.

Here, I am going to break each tissue section into connective and epithelium, and then model differences:

Code

distance <- read_csv("data/Target cells R21 DISTANCE.csv") |>
  janitor::clean_names(replace=janitor:::mu_to_u) |> 
  mutate(donor = factor(donor),
         replicate = factor(replicate))

mean_dist <- distance |>
  dplyr::group_by(condition, group, layer, donor, tissue, target_cell) |>
  dplyr::summarize(mean_distance_to_annotation_with_epithelium_um = mean(distance_to_annotation_with_epithelium_um))

connective <- mean_dist |> 
  dplyr::filter(layer == "Connective") |>
  dplyr::rename("treat_group" = "group")

model_connective <- lme4::lmer(log10(mean_distance_to_annotation_with_epithelium_um) ~ condition*treat_group*target_cell*tissue+(1|donor), 
                          data = connective)


comps_to_make <- c("treat_group",
                   "tissue",
                   "condition",
                   #"target_cell",
                   "condition | treat_group",
                   "condition | treat_group | target_cell",
                   "treat_group | condition | target_cell",
                   "condition | treat_group | target_cell | tissue",
                   "tissue | treat_group | target_cell | condition",
                   #"target_cell | condition | treat_group | layer",
                   "treat_group | condition | target_cell | tissue")

comparisons_made <- compare_pairs(model_connective, 
                                  comparisons = comps_to_make,
                                  p_adjustment = 'fdr')


display_comparison_table(comparisons_made, title = 'connective table')

connective table
treat_group	target_cell	condition	tissue	contrast	estimate	SE	d.f.	t-ratio	p value
.	.	.	.	4h - Non infected	NA	NA	NA	NA	NA
.	.	.	.	Glans - Shaft	NA	NA	NA	NA	NA
.	.	.	.	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
4h	.	.	.	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
Non infected	.	.	.	Circumcised - Uncircumcised	0.01	0.04	96.50	0.28	0.99016
4h	CCR10	.	.	Circumcised - Uncircumcised	-0.18	0.07	540.89	-2.40	0.16638
Non infected	CCR10	.	.	Circumcised - Uncircumcised	-0.01	0.06	407.43	-0.11	0.99016
4h	CD3	.	.	Circumcised - Uncircumcised	-0.02	0.06	472.12	-0.35	0.99016
Non infected	CD3	.	.	Circumcised - Uncircumcised	0.11	0.12	616.88	0.90	0.85798
4h	CD3+CCR10	.	.	Circumcised - Uncircumcised	-0.07	0.04	203.63	-1.68	0.44233
Non infected	CD3+CCR10	.	.	Circumcised - Uncircumcised	0.01	0.04	215.88	0.27	0.99016
4h	CD4	.	.	Circumcised - Uncircumcised	-0.10	0.05	266.76	-1.98	0.30839
Non infected	CD4	.	.	Circumcised - Uncircumcised	0.00	0.05	218.33	-0.08	0.99016
4h	CD4+CCR10	.	.	Circumcised - Uncircumcised	-0.01	0.06	407.80	-0.12	0.99016
Non infected	CD4+CCR10	.	.	Circumcised - Uncircumcised	-0.04	0.05	290.57	-0.75	0.87741
4h	CD4+CD3	.	.	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
Non infected	CD4+CD3	.	.	Circumcised - Uncircumcised	0.00	0.10	605.86	0.04	0.99039
4h	CD4+CD3+CCR10	.	.	Circumcised - Uncircumcised	-0.04	0.04	206.63	-0.79	0.85798
Non infected	CD4+CD3+CCR10	.	.	Circumcised - Uncircumcised	0.00	0.04	215.88	-0.09	0.99016
.	CCR10	Circumcised	.	4h - Non infected	-0.10	0.06	585.81	-1.60	0.49124
.	CCR10	Uncircumcised	.	4h - Non infected	0.07	0.06	588.23	1.14	0.69224
.	CD3	Circumcised	.	4h - Non infected	0.14	0.10	589.18	1.44	0.54127
.	CD3	Uncircumcised	.	4h - Non infected	0.27	0.08	585.88	3.38	0.01653
.	CD3+CCR10	Circumcised	.	4h - Non infected	-0.03	0.04	579.32	-0.80	0.85798
.	CD3+CCR10	Uncircumcised	.	4h - Non infected	0.06	0.04	587.02	1.53	0.54127
.	CD4	Circumcised	.	4h - Non infected	-0.01	0.04	580.82	-0.18	0.99016
.	CD4	Uncircumcised	.	4h - Non infected	0.09	0.04	587.92	2.08	0.27993
.	CD4+CCR10	Circumcised	.	4h - Non infected	0.05	0.05	583.20	0.96	0.83344
.	CD4+CCR10	Uncircumcised	.	4h - Non infected	0.02	0.04	587.80	0.48	0.94613
.	CD4+CD3	Circumcised	.	4h - Non infected	-0.02	0.08	585.80	-0.23	0.99016
.	CD4+CD3	Uncircumcised	.	4h - Non infected	NA	NA	NA	NA	NA
.	CD4+CD3+CCR10	Circumcised	.	4h - Non infected	0.02	0.04	579.47	0.61	0.87820
.	CD4+CD3+CCR10	Uncircumcised	.	4h - Non infected	0.05	0.04	587.02	1.39	0.55749
4h	CCR10	.	Glans	Circumcised - Uncircumcised	-0.35	0.10	612.26	-3.41	0.01653
Non infected	CCR10	.	Glans	Circumcised - Uncircumcised	0.00	0.09	590.04	-0.04	0.99039
4h	CD3	.	Glans	Circumcised - Uncircumcised	-0.12	0.09	589.67	-1.45	0.54127
Non infected	CD3	.	Glans	Circumcised - Uncircumcised	0.28	0.20	606.21	1.44	0.54127
4h	CD3+CCR10	.	Glans	Circumcised - Uncircumcised	-0.12	0.06	398.52	-2.05	0.27993
Non infected	CD3+CCR10	.	Glans	Circumcised - Uncircumcised	-0.01	0.06	416.68	-0.20	0.99016
4h	CD4	.	Glans	Circumcised - Uncircumcised	-0.26	0.07	516.89	-3.74	0.01105
Non infected	CD4	.	Glans	Circumcised - Uncircumcised	-0.04	0.06	416.68	-0.73	0.87820
4h	CD4+CCR10	.	Glans	Circumcised - Uncircumcised	-0.01	0.09	602.60	-0.07	0.99016
Non infected	CD4+CCR10	.	Glans	Circumcised - Uncircumcised	-0.12	0.07	527.56	-1.76	0.38631
4h	CD4+CD3	.	Glans	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
Non infected	CD4+CD3	.	Glans	Circumcised - Uncircumcised	-0.03	0.14	615.07	-0.18	0.99016
4h	CD4+CD3+CCR10	.	Glans	Circumcised - Uncircumcised	-0.08	0.06	406.61	-1.37	0.56124
Non infected	CD4+CD3+CCR10	.	Glans	Circumcised - Uncircumcised	-0.04	0.06	416.68	-0.72	0.87820
4h	CCR10	.	Shaft	Circumcised - Uncircumcised	0.00	0.10	610.50	-0.02	0.99039
Non infected	CCR10	.	Shaft	Circumcised - Uncircumcised	-0.01	0.07	528.07	-0.13	0.99016
4h	CD3	.	Shaft	Circumcised - Uncircumcised	0.08	0.09	596.36	0.88	0.85798
Non infected	CD3	.	Shaft	Circumcised - Uncircumcised	-0.07	0.12	616.98	-0.59	0.87820
4h	CD3+CCR10	.	Shaft	Circumcised - Uncircumcised	-0.03	0.06	390.47	-0.55	0.90061
Non infected	CD3+CCR10	.	Shaft	Circumcised - Uncircumcised	0.04	0.06	404.14	0.63	0.87820
4h	CD4	.	Shaft	Circumcised - Uncircumcised	0.07	0.06	398.83	1.18	0.67998
Non infected	CD4	.	Shaft	Circumcised - Uncircumcised	0.04	0.06	410.63	0.62	0.87820
4h	CD4+CCR10	.	Shaft	Circumcised - Uncircumcised	-0.01	0.06	452.02	-0.13	0.99016
Non infected	CD4+CCR10	.	Shaft	Circumcised - Uncircumcised	0.05	0.06	439.34	0.83	0.85798
4h	CD4+CD3	.	Shaft	Circumcised - Uncircumcised	-0.01	0.08	578.54	-0.14	0.99016
Non infected	CD4+CD3	.	Shaft	Circumcised - Uncircumcised	0.03	0.12	616.93	0.26	0.99016
4h	CD4+CD3+CCR10	.	Shaft	Circumcised - Uncircumcised	0.01	0.06	390.47	0.16	0.99016
Non infected	CD4+CD3+CCR10	.	Shaft	Circumcised - Uncircumcised	0.03	0.06	404.14	0.60	0.87820
4h	CCR10	Circumcised	.	Glans - Shaft	-0.26	0.11	591.05	-2.41	0.16638
Non infected	CCR10	Circumcised	.	Glans - Shaft	0.10	0.07	586.11	1.32	0.59404
4h	CD3	Circumcised	.	Glans - Shaft	0.03	0.08	588.43	0.38	0.99016
Non infected	CD3	Circumcised	.	Glans - Shaft	0.21	0.18	591.10	1.11	0.69224
4h	CD3+CCR10	Circumcised	.	Glans - Shaft	0.02	0.05	579.43	0.38	0.99016
Non infected	CD3+CCR10	Circumcised	.	Glans - Shaft	-0.03	0.05	580.46	-0.69	0.87820
4h	CD4	Circumcised	.	Glans - Shaft	-0.04	0.06	582.25	-0.65	0.87820
Non infected	CD4	Circumcised	.	Glans - Shaft	-0.01	0.05	580.95	-0.27	0.99016
4h	CD4+CCR10	Circumcised	.	Glans - Shaft	0.13	0.09	590.64	1.47	0.54127
Non infected	CD4+CCR10	Circumcised	.	Glans - Shaft	-0.04	0.06	583.16	-0.63	0.87820
4h	CD4+CD3	Circumcised	.	Glans - Shaft	0.13	0.07	584.92	1.82	0.35980
Non infected	CD4+CD3	Circumcised	.	Glans - Shaft	0.16	0.14	590.18	1.19	0.67998
4h	CD4+CD3+CCR10	Circumcised	.	Glans - Shaft	0.00	0.05	579.87	0.09	0.99016
Non infected	CD4+CD3+CCR10	Circumcised	.	Glans - Shaft	-0.03	0.05	580.46	-0.59	0.87820
4h	CCR10	Uncircumcised	.	Glans - Shaft	0.09	0.09	583.57	1.03	0.76798
Non infected	CCR10	Uncircumcised	.	Glans - Shaft	0.09	0.07	587.46	1.23	0.67397
4h	CD3	Uncircumcised	.	Glans - Shaft	0.23	0.09	592.93	2.71	0.09242
Non infected	CD3	Uncircumcised	.	Glans - Shaft	-0.15	0.14	588.71	-1.11	0.69224
4h	CD3+CCR10	Uncircumcised	.	Glans - Shaft	0.11	0.05	579.14	2.05	0.27993
Non infected	CD3+CCR10	Uncircumcised	.	Glans - Shaft	0.01	0.06	579.81	0.26	0.99016
4h	CD4	Uncircumcised	.	Glans - Shaft	0.29	0.06	582.65	4.83	0.00019
Non infected	CD4	Uncircumcised	.	Glans - Shaft	0.07	0.06	579.81	1.19	0.67998
4h	CD4+CCR10	Uncircumcised	.	Glans - Shaft	0.13	0.05	581.07	2.45	0.16638
Non infected	CD4+CCR10	Uncircumcised	.	Glans - Shaft	0.14	0.06	584.02	2.15	0.27993
4h	CD4+CD3	Uncircumcised	.	Glans - Shaft	NA	NA	NA	NA	NA
Non infected	CD4+CD3	Uncircumcised	.	Glans - Shaft	0.22	0.12	586.07	1.84	0.35980
4h	CD4+CD3+CCR10	Uncircumcised	.	Glans - Shaft	0.09	0.05	579.14	1.82	0.35980
Non infected	CD4+CD3+CCR10	Uncircumcised	.	Glans - Shaft	0.05	0.06	579.81	0.86	0.85798
.	CCR10	Circumcised	Glans	4h - Non infected	-0.28	0.10	589.32	-2.82	0.07556
.	CCR10	Uncircumcised	Glans	4h - Non infected	0.06	0.08	588.00	0.79	0.85798
.	CD3	Circumcised	Glans	4h - Non infected	0.06	0.17	590.34	0.35	0.99016
.	CD3	Uncircumcised	Glans	4h - Non infected	0.47	0.13	583.55	3.62	0.01133
.	CD3+CCR10	Circumcised	Glans	4h - Non infected	0.00	0.05	578.22	-0.03	0.99039
.	CD3+CCR10	Uncircumcised	Glans	4h - Non infected	0.10	0.05	584.37	1.92	0.33244
.	CD4	Circumcised	Glans	4h - Non infected	-0.02	0.06	580.89	-0.33	0.99016
.	CD4	Uncircumcised	Glans	4h - Non infected	0.20	0.06	585.69	3.21	0.02537
.	CD4+CCR10	Circumcised	Glans	4h - Non infected	0.14	0.09	585.40	1.50	0.54127
.	CD4+CCR10	Uncircumcised	Glans	4h - Non infected	0.02	0.06	586.63	0.26	0.99016
.	CD4+CD3	Circumcised	Glans	4h - Non infected	-0.04	0.12	587.82	-0.29	0.99016
.	CD4+CD3	Uncircumcised	Glans	4h - Non infected	NA	NA	NA	NA	NA
.	CD4+CD3+CCR10	Circumcised	Glans	4h - Non infected	0.04	0.05	578.61	0.75	0.87741
.	CD4+CD3+CCR10	Uncircumcised	Glans	4h - Non infected	0.08	0.05	584.37	1.40	0.55749
.	CCR10	Circumcised	Shaft	4h - Non infected	0.07	0.08	584.69	0.90	0.85798
.	CCR10	Uncircumcised	Shaft	4h - Non infected	0.07	0.08	585.96	0.83	0.85798
.	CD3	Circumcised	Shaft	4h - Non infected	0.23	0.11	585.40	2.08	0.27993
.	CD3	Uncircumcised	Shaft	4h - Non infected	0.08	0.10	588.76	0.82	0.85798
.	CD3+CCR10	Circumcised	Shaft	4h - Non infected	-0.05	0.05	580.46	-1.11	0.69224
.	CD3+CCR10	Uncircumcised	Shaft	4h - Non infected	0.01	0.05	583.33	0.23	0.99016
.	CD4	Circumcised	Shaft	4h - Non infected	0.00	0.05	580.95	0.09	0.99016
.	CD4	Uncircumcised	Shaft	4h - Non infected	-0.03	0.05	584.05	-0.50	0.94146
.	CD4+CCR10	Circumcised	Shaft	4h - Non infected	-0.03	0.06	582.15	-0.60	0.87820
.	CD4+CCR10	Uncircumcised	Shaft	4h - Non infected	0.02	0.06	584.34	0.44	0.98052
.	CD4+CD3	Circumcised	Shaft	4h - Non infected	0.00	0.09	585.09	0.00	0.99737
.	CD4+CD3	Uncircumcised	Shaft	4h - Non infected	0.04	0.11	586.31	0.41	0.99016
.	CD4+CD3+CCR10	Circumcised	Shaft	4h - Non infected	0.00	0.05	580.46	0.09	0.99016
.	CD4+CD3+CCR10	Uncircumcised	Shaft	4h - Non infected	0.03	0.05	583.33	0.56	0.89838
P value adjustment: FDR

We can also plot some of this data to investigate differences:

Code

load("figures/plots/connective_layer_plot.rda")
connective_layer_plot

However, when we do the same with just cells from the epithelial layer, there aren’t any significant differences. We can go back to our glans/shaft split, modeling glans first:

Glans vs Shaft

Code

glans <- mean_dist |> 
  filter(tissue == 'Glans') |>
  dplyr::rename("treat_group" = "group")

model_glans <- lme4::lmer(log10(mean_distance_to_annotation_with_epithelium_um) ~ condition*treat_group*layer*target_cell+(1|donor), 
                          data = glans)

comps_to_make <- c("treat_group",
                   "layer",
                   "condition",
                   #"target_cell",
                   "condition | treat_group",
                   "condition | treat_group | target_cell",
                   "treat_group | condition | target_cell",
                   "condition | treat_group | target_cell | layer",
                   #"target_cell | condition | treat_group | layer",
                   "treat_group | condition | target_cell | layer")

comparisons_made <- compare_pairs(model_glans, 
                                  comparisons = comps_to_make,
                                  p_adjustment = 'fdr')


display_comparison_table(comparisons_made, title = 'glans table')

glans table
treat_group	target_cell	condition	layer	contrast	estimate	SE	d.f.	t-ratio	p value
.	.	.	.	4h - Non infected	NA	NA	NA	NA	NA
.	.	.	.	Connective - Epithelium	NA	NA	NA	NA	NA
.	.	.	.	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
4h	.	.	.	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
Non infected	.	.	.	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
4h	CCR10	.	.	Circumcised - Uncircumcised	0.09	0.10	388.47	0.97	0.74601
Non infected	CCR10	.	.	Circumcised - Uncircumcised	-0.03	0.10	388.37	-0.29	0.91152
4h	CD3	.	.	Circumcised - Uncircumcised	-0.01	0.09	324.94	-0.13	0.97563
Non infected	CD3	.	.	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
4h	CD3+CCR10	.	.	Circumcised - Uncircumcised	-0.09	0.06	128.88	-1.51	0.44542
Non infected	CD3+CCR10	.	.	Circumcised - Uncircumcised	0.03	0.06	137.40	0.41	0.86213
4h	CD4	.	.	Circumcised - Uncircumcised	-0.11	0.07	221.64	-1.53	0.44542
Non infected	CD4	.	.	Circumcised - Uncircumcised	-0.03	0.06	152.12	-0.40	0.86213
4h	CD4+CCR10	.	.	Circumcised - Uncircumcised	-0.10	0.13	476.14	-0.83	0.74870
Non infected	CD4+CCR10	.	.	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
4h	CD4+CD3	.	.	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
Non infected	CD4+CD3	.	.	Circumcised - Uncircumcised	0.23	0.16	492.50	1.44	0.46014
4h	CD4+CD3+CCR10	.	.	Circumcised - Uncircumcised	-0.06	0.06	136.80	-1.01	0.74601
Non infected	CD4+CD3+CCR10	.	.	Circumcised - Uncircumcised	0.00	0.06	143.72	0.04	0.97841
.	CCR10	Circumcised	.	4h - Non infected	-0.14	0.09	464.10	-1.56	0.44542
.	CCR10	Uncircumcised	.	4h - Non infected	-0.26	0.09	465.23	-2.95	0.05893
.	CD3	Circumcised	.	4h - Non infected	NA	NA	NA	NA	NA
.	CD3	Uncircumcised	.	4h - Non infected	0.20	0.11	463.47	1.76	0.44542
.	CD3+CCR10	Circumcised	.	4h - Non infected	-0.02	0.04	457.18	-0.53	0.83178
.	CD3+CCR10	Uncircumcised	.	4h - Non infected	0.09	0.05	470.89	1.91	0.35715
.	CD4	Circumcised	.	4h - Non infected	0.04	0.05	460.64	0.79	0.76750
.	CD4	Uncircumcised	.	4h - Non infected	0.13	0.06	468.74	2.27	0.20872
.	CD4+CCR10	Circumcised	.	4h - Non infected	0.20	0.13	463.93	1.48	0.44542
.	CD4+CCR10	Uncircumcised	.	4h - Non infected	NA	NA	NA	NA	NA
.	CD4+CD3	Circumcised	.	4h - Non infected	-0.09	0.12	469.98	-0.74	0.78521
.	CD4+CD3	Uncircumcised	.	4h - Non infected	NA	NA	NA	NA	NA
.	CD4+CD3+CCR10	Circumcised	.	4h - Non infected	0.03	0.05	458.52	0.65	0.81030
.	CD4+CD3+CCR10	Uncircumcised	.	4h - Non infected	0.09	0.05	465.10	1.92	0.35715
4h	CCR10	.	Connective	Circumcised - Uncircumcised	-0.31	0.13	480.99	-2.38	0.17849
Non infected	CCR10	.	Connective	Circumcised - Uncircumcised	-0.01	0.11	445.06	-0.07	0.97563
4h	CD3	.	Connective	Circumcised - Uncircumcised	-0.09	0.11	445.05	-0.85	0.74601
Non infected	CD3	.	Connective	Circumcised - Uncircumcised	0.48	0.25	484.77	1.93	0.35715
4h	CD3+CCR10	.	Connective	Circumcised - Uncircumcised	-0.11	0.08	253.64	-1.51	0.44542
Non infected	CD3+CCR10	.	Connective	Circumcised - Uncircumcised	-0.01	0.08	267.69	-0.09	0.97563
4h	CD4	.	Connective	Circumcised - Uncircumcised	-0.23	0.09	358.40	-2.56	0.15208
Non infected	CD4	.	Connective	Circumcised - Uncircumcised	-0.04	0.08	267.69	-0.49	0.83178
4h	CD4+CCR10	.	Connective	Circumcised - Uncircumcised	0.02	0.12	465.17	0.14	0.97563
Non infected	CD4+CCR10	.	Connective	Circumcised - Uncircumcised	-0.15	0.09	369.39	-1.63	0.44542
4h	CD4+CD3	.	Connective	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
Non infected	CD4+CD3	.	Connective	Circumcised - Uncircumcised	0.11	0.18	493.72	0.60	0.81030
4h	CD4+CD3+CCR10	.	Connective	Circumcised - Uncircumcised	-0.07	0.08	259.93	-0.98	0.74601
Non infected	CD4+CD3+CCR10	.	Connective	Circumcised - Uncircumcised	-0.04	0.08	267.69	-0.48	0.83178
4h	CCR10	.	Epithelium	Circumcised - Uncircumcised	0.50	0.13	478.61	3.88	0.00416
Non infected	CCR10	.	Epithelium	Circumcised - Uncircumcised	-0.05	0.15	490.64	-0.33	0.90650
4h	CD3	.	Epithelium	Circumcised - Uncircumcised	0.07	0.12	461.80	0.61	0.81030
Non infected	CD3	.	Epithelium	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
4h	CD3+CCR10	.	Epithelium	Circumcised - Uncircumcised	-0.07	0.08	253.64	-0.90	0.74601
Non infected	CD3+CCR10	.	Epithelium	Circumcised - Uncircumcised	0.06	0.08	267.69	0.75	0.78521
4h	CD4	.	Epithelium	Circumcised - Uncircumcised	0.01	0.10	398.18	0.09	0.97563
Non infected	CD4	.	Epithelium	Circumcised - Uncircumcised	-0.01	0.08	314.11	-0.15	0.97563
4h	CD4+CCR10	.	Epithelium	Circumcised - Uncircumcised	-0.23	0.21	489.33	-1.05	0.73842
Non infected	CD4+CCR10	.	Epithelium	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
4h	CD4+CD3	.	Epithelium	Circumcised - Uncircumcised	NA	NA	NA	NA	NA
Non infected	CD4+CD3	.	Epithelium	Circumcised - Uncircumcised	0.35	0.25	484.83	1.40	0.47447
4h	CD4+CD3+CCR10	.	Epithelium	Circumcised - Uncircumcised	-0.05	0.08	273.90	-0.63	0.81030
Non infected	CD4+CD3+CCR10	.	Epithelium	Circumcised - Uncircumcised	0.04	0.08	288.62	0.53	0.83178
.	CCR10	Circumcised	Connective	4h - Non infected	-0.21	0.12	465.02	-1.72	0.44542
.	CCR10	Uncircumcised	Connective	4h - Non infected	0.09	0.10	467.59	0.86	0.74601
.	CD3	Circumcised	Connective	4h - Non infected	-0.01	0.21	464.97	-0.07	0.97563
.	CD3	Uncircumcised	Connective	4h - Non infected	0.56	0.16	460.68	3.47	0.01343
.	CD3+CCR10	Circumcised	Connective	4h - Non infected	0.00	0.06	457.18	-0.03	0.97841
.	CD3+CCR10	Uncircumcised	Connective	4h - Non infected	0.10	0.07	464.50	1.55	0.44542
.	CD4	Circumcised	Connective	4h - Non infected	-0.01	0.07	459.17	-0.11	0.97563
.	CD4	Uncircumcised	Connective	4h - Non infected	0.18	0.08	463.70	2.38	0.17849
.	CD4+CCR10	Circumcised	Connective	4h - Non infected	0.17	0.11	461.83	1.53	0.44542
.	CD4+CCR10	Uncircumcised	Connective	4h - Non infected	0.01	0.08	465.89	0.08	0.97563
.	CD4+CD3	Circumcised	Connective	4h - Non infected	-0.09	0.15	465.07	-0.59	0.81030
.	CD4+CD3	Uncircumcised	Connective	4h - Non infected	NA	NA	NA	NA	NA
.	CD4+CD3+CCR10	Circumcised	Connective	4h - Non infected	0.04	0.06	457.67	0.63	0.81030
.	CD4+CD3+CCR10	Uncircumcised	Connective	4h - Non infected	0.08	0.07	464.50	1.14	0.65834
.	CCR10	Circumcised	Epithelium	4h - Non infected	-0.06	0.12	463.09	-0.47	0.83182
.	CCR10	Uncircumcised	Epithelium	4h - Non infected	-0.60	0.14	461.40	-4.32	0.00135
.	CD3	Circumcised	Epithelium	4h - Non infected	NA	NA	NA	NA	NA
.	CD3	Uncircumcised	Epithelium	4h - Non infected	-0.15	0.16	464.05	-0.95	0.74601
.	CD3+CCR10	Circumcised	Epithelium	4h - Non infected	-0.05	0.06	457.18	-0.72	0.78938
.	CD3+CCR10	Uncircumcised	Epithelium	4h - Non infected	0.08	0.07	464.50	1.18	0.65834
.	CD4	Circumcised	Epithelium	4h - Non infected	0.09	0.08	460.93	1.15	0.65834
.	CD4	Uncircumcised	Epithelium	4h - Non infected	0.07	0.08	465.27	0.89	0.74601
.	CD4+CCR10	Circumcised	Epithelium	4h - Non infected	0.22	0.24	465.20	0.92	0.74601
.	CD4+CCR10	Uncircumcised	Epithelium	4h - Non infected	NA	NA	NA	NA	NA
.	CD4+CD3	Circumcised	Epithelium	4h - Non infected	-0.08	0.17	463.82	-0.48	0.83178
.	CD4+CD3	Uncircumcised	Epithelium	4h - Non infected	NA	NA	NA	NA	NA
.	CD4+CD3+CCR10	Circumcised	Epithelium	4h - Non infected	0.02	0.07	458.27	0.30	0.91152
.	CD4+CD3+CCR10	Uncircumcised	Epithelium	4h - Non infected	0.11	0.07	460.05	1.58	0.44542
P value adjustment: FDR

We can also visualize some of these differences:

Code

load("figures/plots/glans_if_plot.rda")
glans_if_plot

This is in contrast to doing the same comparisons on just the shaft data, which did not yield any signficiant differences in distance from epithelium.

As a last check– when we split the data by uncircumcised and circumcised do we see anything?

Uncircumcised vs circumcised

We see some differences with the uncircumcised data alone, as shown below:

Code

uncut <- mean_dist |> 
  dplyr::filter(condition == "Uncircumcised") |>
  dplyr::rename("treat_group" = "group")

model_uncut <- lme4::lmer(log10(mean_distance_to_annotation_with_epithelium_um) ~ layer*treat_group*target_cell*tissue+(1|donor), 
                               data = uncut)

comps_to_make <- c("treat_group",
                   "tissue",
                   #"layer",
                   #"target_cell",
                   #"layer | treat_group",
                   #"layer | treat_group | target_cell",
                   "treat_group | tissue | target_cell",
                   #"layer | treat_group | target_cell | tissue",
                   "tissue | treat_group | target_cell | layer",
                   #"target_cell | condition | treat_group | layer",
                   "treat_group | layer | target_cell | tissue"
                   )

comparisons_made <- compare_pairs(model_uncut, 
                                  comparisons = comps_to_make,
                                  p_adjustment = 'fdr')

display_comparison_table(comparisons_made, title = 'Uncircumcised table')

Uncircumcised table
tissue	target_cell	treat_group	layer	contrast	estimate	SE	d.f.	t-ratio	p value
.	.	.	.	4h - Non infected	NA	NA	NA	NA	NA
.	.	.	.	Glans - Shaft	NA	NA	NA	NA	NA
Glans	CCR10	.	.	4h - Non infected	-0.25	0.09	504.14	-2.74	0.09345
Shaft	CCR10	.	.	4h - Non infected	0.02	0.08	505.28	0.22	0.90419
Glans	CD3	.	.	4h - Non infected	0.13	0.12	503.79	1.10	0.59588
Shaft	CD3	.	.	4h - Non infected	NA	NA	NA	NA	NA
Glans	CD3+CCR10	.	.	4h - Non infected	0.09	0.05	505.42	1.74	0.34549
Shaft	CD3+CCR10	.	.	4h - Non infected	0.02	0.05	504.58	0.37	0.90419
Glans	CD4	.	.	4h - Non infected	0.12	0.06	505.78	2.01	0.30208
Shaft	CD4	.	.	4h - Non infected	0.04	0.06	504.87	0.64	0.85855
Glans	CD4+CCR10	.	.	4h - Non infected	NA	NA	NA	NA	NA
Shaft	CD4+CCR10	.	.	4h - Non infected	0.02	0.06	503.07	0.24	0.90419
Glans	CD4+CD3	.	.	4h - Non infected	NA	NA	NA	NA	NA
Shaft	CD4+CD3	.	.	4h - Non infected	0.06	0.10	506.44	0.62	0.85855
Glans	CD4+CD3+CCR10	.	.	4h - Non infected	0.09	0.05	503.44	1.80	0.33193
Shaft	CD4+CD3+CCR10	.	.	4h - Non infected	-0.03	0.05	504.89	-0.56	0.86932
.	CCR10	4h	Connective	Glans - Shaft	0.09	0.11	502.48	0.81	0.78852
.	CCR10	Non infected	Connective	Glans - Shaft	0.11	0.10	504.29	1.12	0.59588
.	CD3	4h	Connective	Glans - Shaft	0.21	0.11	506.36	1.84	0.33193
.	CD3	Non infected	Connective	Glans - Shaft	-0.20	0.18	504.60	-1.12	0.59588
.	CD3+CCR10	4h	Connective	Glans - Shaft	0.10	0.07	500.59	1.55	0.44960
.	CD3+CCR10	Non infected	Connective	Glans - Shaft	0.02	0.07	500.89	0.24	0.90419
.	CD4	4h	Connective	Glans - Shaft	0.29	0.08	502.07	3.69	0.00728
.	CD4	Non infected	Connective	Glans - Shaft	0.07	0.07	500.89	0.95	0.67222
.	CD4+CCR10	4h	Connective	Glans - Shaft	0.13	0.07	501.45	1.85	0.33193
.	CD4+CCR10	Non infected	Connective	Glans - Shaft	0.16	0.09	502.77	1.82	0.33193
.	CD4+CD3	4h	Connective	Glans - Shaft	NA	NA	NA	NA	NA
.	CD4+CD3	Non infected	Connective	Glans - Shaft	0.20	0.16	503.48	1.28	0.56706
.	CD4+CD3+CCR10	4h	Connective	Glans - Shaft	0.09	0.07	500.59	1.37	0.53221
.	CD4+CD3+CCR10	Non infected	Connective	Glans - Shaft	0.05	0.07	500.89	0.70	0.85855
.	CCR10	4h	Epithelium	Glans - Shaft	-0.22	0.13	506.07	-1.68	0.37176
.	CCR10	Non infected	Epithelium	Glans - Shaft	0.30	0.14	505.30	2.13	0.28128
.	CD3	4h	Epithelium	Glans - Shaft	0.00	0.13	504.75	0.00	0.99734
.	CD3	Non infected	Epithelium	Glans - Shaft	NA	NA	NA	NA	NA
.	CD3+CCR10	4h	Epithelium	Glans - Shaft	0.13	0.07	500.59	2.00	0.30208
.	CD3+CCR10	Non infected	Epithelium	Glans - Shaft	0.08	0.07	500.89	1.15	0.59588
.	CD4	4h	Epithelium	Glans - Shaft	0.01	0.09	503.32	0.06	0.99626
.	CD4	Non infected	Epithelium	Glans - Shaft	0.06	0.08	501.80	0.79	0.78852
.	CD4+CCR10	4h	Epithelium	Glans - Shaft	0.04	0.10	503.97	0.44	0.90419
.	CD4+CCR10	Non infected	Epithelium	Glans - Shaft	NA	NA	NA	NA	NA
.	CD4+CD3	4h	Epithelium	Glans - Shaft	NA	NA	NA	NA	NA
.	CD4+CD3	Non infected	Epithelium	Glans - Shaft	0.07	0.23	505.39	0.28	0.90419
.	CD4+CD3+CCR10	4h	Epithelium	Glans - Shaft	0.18	0.07	501.60	2.57	0.12172
.	CD4+CD3+CCR10	Non infected	Epithelium	Glans - Shaft	-0.02	0.07	500.48	-0.23	0.90419
Glans	CCR10	.	Connective	4h - Non infected	0.05	0.11	504.39	0.49	0.90419
Glans	CCR10	.	Epithelium	4h - Non infected	-0.55	0.15	502.62	-3.77	0.00728
Glans	CD3	.	Connective	4h - Non infected	0.49	0.17	502.50	2.89	0.07956
Glans	CD3	.	Epithelium	4h - Non infected	-0.22	0.17	503.45	-1.33	0.54792
Glans	CD3+CCR10	.	Connective	4h - Non infected	0.10	0.07	502.87	1.41	0.51787
Glans	CD3+CCR10	.	Epithelium	4h - Non infected	0.07	0.07	502.87	1.06	0.60880
Glans	CD4	.	Connective	4h - Non infected	0.20	0.08	503.25	2.44	0.14728
Glans	CD4	.	Epithelium	4h - Non infected	0.04	0.08	504.15	0.46	0.90419
Glans	CD4+CCR10	.	Connective	4h - Non infected	0.00	0.08	503.85	0.05	0.99626
Glans	CD4+CCR10	.	Epithelium	4h - Non infected	NA	NA	NA	NA	NA
Glans	CD4+CD3	.	Connective	4h - Non infected	NA	NA	NA	NA	NA
Glans	CD4+CD3	.	Epithelium	4h - Non infected	NA	NA	NA	NA	NA
Glans	CD4+CD3+CCR10	.	Connective	4h - Non infected	0.07	0.07	502.87	1.02	0.62602
Glans	CD4+CD3+CCR10	.	Epithelium	4h - Non infected	0.11	0.07	501.44	1.51	0.45321
Shaft	CCR10	.	Connective	4h - Non infected	0.07	0.11	503.47	0.65	0.85855
Shaft	CCR10	.	Epithelium	4h - Non infected	-0.03	0.12	506.05	-0.28	0.90419
Shaft	CD3	.	Connective	4h - Non infected	0.08	0.13	504.66	0.62	0.85855
Shaft	CD3	.	Epithelium	4h - Non infected	NA	NA	NA	NA	NA
Shaft	CD3+CCR10	.	Connective	4h - Non infected	0.01	0.07	502.42	0.19	0.91116
Shaft	CD3+CCR10	.	Epithelium	4h - Non infected	0.02	0.07	502.42	0.33	0.90419
Shaft	CD4	.	Connective	4h - Non infected	-0.02	0.07	502.75	-0.35	0.90419
Shaft	CD4	.	Epithelium	4h - Non infected	0.10	0.08	503.39	1.13	0.59588
Shaft	CD4+CCR10	.	Connective	4h - Non infected	0.03	0.07	502.79	0.39	0.90419
Shaft	CD4+CCR10	.	Epithelium	4h - Non infected	0.00	0.10	502.64	0.03	0.99626
Shaft	CD4+CD3	.	Connective	4h - Non infected	0.04	0.14	503.53	0.29	0.90419
Shaft	CD4+CD3	.	Epithelium	4h - Non infected	0.09	0.15	505.72	0.59	0.86242
Shaft	CD4+CD3+CCR10	.	Connective	4h - Non infected	0.03	0.07	502.42	0.44	0.90419
Shaft	CD4+CD3+CCR10	.	Epithelium	4h - Non infected	-0.09	0.07	502.91	-1.21	0.59588
P value adjustment: FDR

Code

load("figures/plots/uncut_if_plot.rda")
uncut_if_plot

However, there is not much reciprocal significance in the circumcised data, and these effect sizes do not seem large:

Code

cut <- mean_dist |> 
  dplyr::filter(condition == "Circumcised") |>
  dplyr::rename("treat_group" = "group")

model_cut <- lme4::lmer(log10(mean_distance_to_annotation_with_epithelium_um) ~ layer*treat_group*target_cell*tissue+(1|donor), 
                          data = cut)

comps_to_make <- c("treat_group",
                   "tissue",
                   #"layer",
                   #"target_cell",
                   #"layer | treat_group",
                   #"layer | treat_group | target_cell",
                   "treat_group | tissue | target_cell",
                   #"layer | treat_group | target_cell | tissue",
                   "tissue | treat_group | target_cell | layer",
                   #"target_cell | condition | treat_group | layer",
                   "treat_group | layer | target_cell | tissue"
)

comparisons_made <- compare_pairs(model_cut, 
                                  comparisons = comps_to_make,
                                  p_adjustment = 'fdr')


display_comparison_table(comparisons_made, title = 'Circumcised table')

Circumcised table
tissue	target_cell	treat_group	layer	contrast	estimate	SE	d.f.	t-ratio	p value
.	.	.	.	4h - Non infected	NA	NA	NA	NA	NA
.	.	.	.	Glans - Shaft	NA	NA	NA	NA	NA
Glans	CCR10	.	.	4h - Non infected	-0.16	0.09	548.90	-1.78	0.55850
Shaft	CCR10	.	.	4h - Non infected	-0.06	0.08	551.56	-0.79	0.88958
Glans	CD3	.	.	4h - Non infected	NA	NA	NA	NA	NA
Shaft	CD3	.	.	4h - Non infected	0.14	0.14	549.80	0.95	0.88756
Glans	CD3+CCR10	.	.	4h - Non infected	-0.02	0.05	545.07	-0.51	0.92366
Shaft	CD3+CCR10	.	.	4h - Non infected	-0.07	0.05	547.22	-1.47	0.72964
Glans	CD4	.	.	4h - Non infected	0.04	0.06	546.90	0.78	0.88958
Shaft	CD4	.	.	4h - Non infected	-0.03	0.05	547.78	-0.54	0.92366
Glans	CD4+CCR10	.	.	4h - Non infected	0.16	0.14	549.31	1.16	0.78357
Shaft	CD4+CCR10	.	.	4h - Non infected	-0.18	0.07	546.88	-2.76	0.13323
Glans	CD4+CD3	.	.	4h - Non infected	-0.08	0.12	551.47	-0.69	0.92366
Shaft	CD4+CD3	.	.	4h - Non infected	-0.02	0.10	548.12	-0.19	0.98975
Glans	CD4+CD3+CCR10	.	.	4h - Non infected	0.03	0.05	545.53	0.58	0.92366
Shaft	CD4+CD3+CCR10	.	.	4h - Non infected	-0.01	0.05	547.58	-0.16	0.98975
.	CCR10	4h	Connective	Glans - Shaft	-0.25	0.14	550.20	-1.80	0.55850
.	CCR10	Non infected	Connective	Glans - Shaft	0.11	0.10	548.36	1.18	0.78357
.	CD3	4h	Connective	Glans - Shaft	0.01	0.11	549.09	0.13	0.98975
.	CD3	Non infected	Connective	Glans - Shaft	0.23	0.24	550.53	0.99	0.87090
.	CD3+CCR10	4h	Connective	Glans - Shaft	0.02	0.07	545.56	0.33	0.98975
.	CD3+CCR10	Non infected	Connective	Glans - Shaft	-0.03	0.06	546.07	-0.50	0.92366
.	CD4	4h	Connective	Glans - Shaft	-0.04	0.07	546.64	-0.50	0.92366
.	CD4	Non infected	Connective	Glans - Shaft	-0.01	0.06	546.28	-0.18	0.98975
.	CD4+CCR10	4h	Connective	Glans - Shaft	0.17	0.12	550.09	1.43	0.72964
.	CD4+CCR10	Non infected	Connective	Glans - Shaft	-0.02	0.07	547.10	-0.32	0.98975
.	CD4+CD3	4h	Connective	Glans - Shaft	0.11	0.09	547.64	1.17	0.78357
.	CD4+CD3	Non infected	Connective	Glans - Shaft	0.20	0.18	550.01	1.13	0.78408
.	CD4+CD3+CCR10	4h	Connective	Glans - Shaft	0.01	0.07	545.74	0.08	0.98975
.	CD4+CD3+CCR10	Non infected	Connective	Glans - Shaft	-0.03	0.06	546.07	-0.42	0.97984
.	CCR10	4h	Epithelium	Glans - Shaft	0.10	0.11	546.66	0.92	0.88958
.	CCR10	Non infected	Epithelium	Glans - Shaft	-0.06	0.13	551.36	-0.50	0.92366
.	CD3	4h	Epithelium	Glans - Shaft	-0.02	0.22	552.31	-0.11	0.98975
.	CD3	Non infected	Epithelium	Glans - Shaft	NA	NA	NA	NA	NA
.	CD3+CCR10	4h	Epithelium	Glans - Shaft	0.11	0.07	545.71	1.62	0.59666
.	CD3+CCR10	Non infected	Epithelium	Glans - Shaft	0.07	0.07	546.49	1.10	0.79519
.	CD4	4h	Epithelium	Glans - Shaft	0.17	0.09	547.09	1.89	0.55850
.	CD4	Non infected	Epithelium	Glans - Shaft	0.00	0.07	546.34	0.04	0.98975
.	CD4+CCR10	4h	Epithelium	Glans - Shaft	-0.17	0.21	550.30	-0.79	0.88958
.	CD4+CCR10	Non infected	Epithelium	Glans - Shaft	-0.66	0.17	550.17	-3.85	0.00870
.	CD4+CD3	4h	Epithelium	Glans - Shaft	0.17	0.14	549.06	1.24	0.78357
.	CD4+CD3	Non infected	Epithelium	Glans - Shaft	0.20	0.19	550.17	1.06	0.80616
.	CD4+CD3+CCR10	4h	Epithelium	Glans - Shaft	0.15	0.07	546.56	2.12	0.45633
.	CD4+CD3+CCR10	Non infected	Epithelium	Glans - Shaft	0.11	0.07	546.65	1.66	0.59014
Glans	CCR10	.	Connective	4h - Non infected	-0.28	0.13	549.44	-2.16	0.45633
Glans	CCR10	.	Epithelium	4h - Non infected	-0.04	0.12	547.80	-0.34	0.98975
Glans	CD3	.	Connective	4h - Non infected	0.03	0.21	550.27	0.13	0.98975
Glans	CD3	.	Epithelium	4h - Non infected	NA	NA	NA	NA	NA
Glans	CD3+CCR10	.	Connective	4h - Non infected	0.00	0.07	545.07	-0.03	0.98975
Glans	CD3+CCR10	.	Epithelium	4h - Non infected	-0.05	0.07	545.07	-0.69	0.92366
Glans	CD4	.	Connective	4h - Non infected	-0.02	0.07	546.08	-0.28	0.98975
Glans	CD4	.	Epithelium	4h - Non infected	0.11	0.08	546.91	1.27	0.78357
Glans	CD4+CCR10	.	Connective	4h - Non infected	0.15	0.12	547.91	1.32	0.78357
Glans	CD4+CCR10	.	Epithelium	4h - Non infected	0.17	0.25	550.32	0.67	0.92366
Glans	CD4+CD3	.	Connective	4h - Non infected	-0.09	0.16	549.01	-0.59	0.92366
Glans	CD4+CD3	.	Epithelium	4h - Non infected	-0.07	0.17	548.31	-0.40	0.98455
Glans	CD4+CD3+CCR10	.	Connective	4h - Non infected	0.04	0.07	545.22	0.56	0.92366
Glans	CD4+CD3+CCR10	.	Epithelium	4h - Non infected	0.02	0.07	545.49	0.27	0.98975
Shaft	CCR10	.	Connective	4h - Non infected	0.08	0.11	547.79	0.78	0.88958
Shaft	CCR10	.	Epithelium	4h - Non infected	-0.21	0.11	550.97	-1.82	0.55850
Shaft	CD3	.	Connective	4h - Non infected	0.25	0.14	547.87	1.72	0.57609
Shaft	CD3	.	Epithelium	4h - Non infected	0.03	0.25	551.51	0.10	0.98975
Shaft	CD3+CCR10	.	Connective	4h - Non infected	-0.05	0.06	546.06	-0.86	0.88958
Shaft	CD3+CCR10	.	Epithelium	4h - Non infected	-0.08	0.07	546.33	-1.21	0.78357
Shaft	CD4	.	Connective	4h - Non infected	0.00	0.06	546.26	0.06	0.98975
Shaft	CD4	.	Epithelium	4h - Non infected	-0.06	0.07	547.26	-0.78	0.88958
Shaft	CD4+CCR10	.	Connective	4h - Non infected	-0.04	0.07	546.70	-0.53	0.92366
Shaft	CD4+CCR10	.	Epithelium	4h - Non infected	-0.32	0.11	547.41	-2.96	0.10689
Shaft	CD4+CD3	.	Connective	4h - Non infected	0.00	0.12	547.83	0.01	0.98975
Shaft	CD4+CD3	.	Epithelium	4h - Non infected	-0.04	0.15	547.02	-0.25	0.98975
Shaft	CD4+CD3+CCR10	.	Connective	4h - Non infected	0.00	0.06	546.06	0.07	0.98975
Shaft	CD4+CD3+CCR10	.	Epithelium	4h - Non infected	-0.02	0.07	547.08	-0.28	0.98975
P value adjustment: FDR

Virion/IF Distance Correlations

Because we also had distance measurements for virion penetration, we can revisit that data and see if there are salient correlations:

Code

load(file = "figures/plots/correlation_plot_1.rda")

correlation_plot_1

Here, we can also zoom in on the tip of the biopsy– as the plot above shows, virions aren’t really penetrating further than 20um. If we just zoom into this area, we can see what % of each cell type is within our “viral range” (here defined as 30um from the epithelium), both in the case where virus was present (4h) and was not (Non infected). Does the presence of virions affect the % of immune cell types at the tip?

Code

load(file = "figures/plots/correlation_plot_2.rda")

correlation_plot_2 +
  theme(axis.text.x = element_text(angle = 90))

Probably not. Maybe something weird (again) happening with the CD4 single positive cells; not sure how relevant this is though and may just reflect a subset of these cells that we don’t have markers to define.